Machine Learning Engineer - Reinforcement Learning
Core
Building training, evaluation, and tooling systems for LLM-powered AI agents and reinforcement learning to enable autonomous supply chain decision-making.
Role type
Senior IC Machine Learning Engineer (Reinforcement Learning & LLM Agents)
Builds
Production AI decision-making products, agent environments, and evaluation frameworks for supply chain optimization.
Domain
Supply chain logistics + Applied AI / Reinforcement Learning
Deliverable
production ML models
Required skills
Reinforcement Learning (RL) with LLMs, LLM fine-tuning, reward modeling, agent environment design, Python, PyTorch, RLHF/RLAIF, policy optimization, data pipeline engineering
Preferred skills
Human-in-the-loop ML systems, evaluation frameworks for open-ended tasks, supply chain/logistics domain knowledge, side projects demonstrating AI tinkering
Technologies
Python, PyTorch, LLMs, RL environments
Responsibilities
Design and implement LLM-powered agent environments for supply chain decision-making; Fine-tune, adapt, and evaluate LLMs for domain-specific reasoning; Design, test, and iterate on reward functions to capture desired agent behaviors; Review LLM traces and rollouts to identify failure modes and reward hacking; Build evaluation frameworks to measure model quality and agent performance; Create data pipelines for training, fine-tuning, and human feedback collection; Develop tooling for building, testing, and deploying AI-assisted workflows.
Seniority
Senior, hands-on IC